Article
Computer Science, Artificial Intelligence
Jorge Martinez-Gil, Jose Manuel Chaves-Gonzalez
Summary: Ontology meta-matching techniques have been established as effective in discovering semantic relationships between independently developed knowledge models. While the resulting models may be difficult for humans to interpret, a novel approach based on Mamdani fuzzy inference aims to improve interpretability by making the models more similar to natural language. Validation with popular ontological models in the biomedical field has shown promising results.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Balachandran Sangeetha, Ranganathan Vidhyapriya
Summary: This research aims to improve the efficiency and automation of ontology mapping in the biomedical domain. Biomedical ontologies are crucial for accurate interpretation of medical records and decision making, but two main challenges are overlapping concepts and a large search space. To address these issues, a distributed environment using the Hadoop framework is implemented, and a Map-Reduce algorithm is employed for parallelizing the mapping system, resulting in significant time reduction. An Extreme Learning Machine based neural network is utilized for precise alignment. Evaluation using OAEI and OBO biomedical ontologies demonstrates notable improvements in execution time and evaluation metrics with the proposed multi-strategy similarity metrics of the ontology mapping system. The mapping between ontologies is represented using the Alignment API, simplifying the calculation process.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Nicolas Ferranti, Jairo Francisco de Souza, Stenio Sa Rosario Furtado Soares
Summary: New ontology matching approaches are published every year to address the heterogeneity problem. Combining different alignment techniques can improve accuracy by capturing more entity characteristics. Local search-based meta-heuristics show good performance and accuracy compared to global optimization meta-heuristics.
KNOWLEDGE AND INFORMATION SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Abdullah Almuhaimeed, Mohammed A. Alhomidi, Mohammed N. Alenezi, Emad Alamoud, Saad Alqahtani
Summary: With the widespread of data resources on the internet, overlapping between these resources can provide researchers with more information. Extracting and calculating the semantic similarity between these resources is a challenging task due to their varying descriptions. To address this issue, the paper presents a new semantic similarity method that considers different factors to calculate the semantic similarity between different resources. By utilizing node descriptions and relations from multiple ontologies, this method strengthens the similarity relations between resources and discovers new semantic similarities.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Qiu Ji, Weizhuo Li, Shiqi Zhou, Guilin Qi, Yuanfang Li
Summary: Ontologies, as the core building blocks of the Semantic Web, provide shared vocabularies and conceptual knowledge for specific application fields. However, logical conflicts often arise in actual application scenarios due to disjointness or negation in the ontologies. Incoherence and inconsistency are two types of logical conflicts. Handling incoherence is important as it can lead to inconsistency and affect the correctness of semantic reasoning. Various incoherent ontologies are essential for evaluating methods to handle incoherence.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Muhammad Ishaq, Abdullah Khan, Muhammad Asim, Asfandyar Khan, Javed Iqbal Bangash
Summary: The development of information technology has brought about innovations in various sectors of bio-sciences. Researchers are utilizing the Semantic Web to improve web search, mining, and integration, thus making it easier to find relevant and high-quality content. This work focuses on selected agri-ontologies with the objective of promoting outcome-based research and expertise sharing.
JOURNAL OF INFORMATION SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Samira Babalou, Alsayed Algergawy, Birgitta Koenig-Ries
Summary: Computing the semantic similarity between pairs of terms is crucial for various shared data applications. One way to determine term similarity is to assess their word similarity using knowledge resources like ontologies or corpora. Information-theoretic approaches have shown promise by computing concept information content from ontologies. Choosing a suitable subsumer, called Consensus Common Subsumer (CCS), among common ancestors of two concepts can impact the quality of term similarity assessment.
DATA & KNOWLEDGE ENGINEERING
(2023)
Article
Computer Science, Information Systems
Xiulei Liu, Qiang Tong, Xuhong Liu, Zhihui Qin
Summary: Information used in existing ontology matching solutions are typically classified into four categories: lexical information, structural information, semantic information, and external information. This paper summarizes and analyzes approaches for utilizing the same kind of information, revealing that lexical information is mainly analyzed based on text and dictionary similarity, while structural and semantic information are mainly analyzed based on graph structure and reasoner. The paper also discusses methods for aggregating information analysis results and provides insights into future research directions.
Article
Mathematical & Computational Biology
Nicolas Matentzoglu, Damien Goutte-Gattat, Shawn Zheng Kai Tan, James P. Balhoff, Seth Carbon, Anita R. Caron, William D. Duncan, Joe E. Flack, Melissa Haendel, Nomi L. Harris, William R. Hogan, Charles Tapley Hoyt, Rebecca C. Jackson, HyeongSik Kim, Huseyin Kir, Martin Larralde, Julie A. McMurry, James A. Overton, Bjoern Peters, Clare Pilgrim, Ray Stefancsik, Sofia M. C. Robb, Sabrina Toro, Nicole A. Vasilevsky, Ramona Walls, Christopher J. Mungall, David Osumi-Sutherland
Summary: This article discusses the complex workflows involved in managing the ontology life cycle and the diverse set of tools required for this process. Standardizing release practices and quality standards are crucial in the biomedical domain to enable interoperability. The article also provides an overview of the Ontology Development Kit (ODK) and its practical applications.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2022)
Article
Computer Science, Information Systems
Rita. T. T. Sousa, Sara Silva, Catia Pesquita
Summary: Semantic similarity plays a crucial role in bioinformatics applications such as protein-protein interaction prediction and disease-gene association discovery. However, existing semantic similarity measures are general-purpose and may not align well with specific biological perspectives. In this study, we introduce a supervised machine learning approach to tailor aspect-oriented semantic similarity measures for different biological views. The results demonstrate the superiority of our method in fitting semantic similarity models to diverse biological perspectives compared to commonly used manual combinations of semantic aspects.
Article
Computer Science, Artificial Intelligence
Cassia Trojahn, Renata Vieira, Daniela Schmidt, Adam Pease, Giancarlo Guizzardi
Summary: Ontology matching is a research area focused on finding ways to make different ontologies interoperable. Foundational ontologies play a crucial role in ontology matching by providing a well-founded reference model that can be shared across domains. This paper provides an overview of the tasks involved in ontology matching considering foundational ontologies, discussing existing proposals' strengths and weaknesses, and highlighting future challenges to be addressed.
Article
Multidisciplinary Sciences
Maulik R. Kamdar, Mark A. Musen
Summary: Despite the efforts to create Life Sciences Linked Open Data (LSLOD) cloud, there are still semantic heterogeneity issues across biomedical linked open data sources. Some sources are standalone, lack inter-linkage, and use unpublished schemas with minimal reuse or mappings. The LSLOD schema graph analysis in this research provides assistance to researchers querying and integrating data from multiple biomedical sources simultaneously on the Web.
Article
Computer Science, Artificial Intelligence
Yasser Maatouk
Summary: AI-SPedia is a repository that contains semantic knowledge of scientific publications related to artificial intelligence (AI). It can evaluate the impact of AI research and answer related questions using smart queries. It is the first attempt to evaluate the impacts of AI scientific publications using both bibliometric and altmetric indicators and the power of semantic web technology.
PEERJ COMPUTER SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Xingsi Xue, Jie Zhang
Summary: A biomedical ontology helps to address data heterogeneity in different databases, but may introduce heterogeneity issue among ontologies. A framework is proposed to partition and match large-scale biomedical ontologies, with algorithms and techniques ensuring efficiency and quality of alignment. Experimental results show significant improvement over existing techniques in aligning biomedical ontologies.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
J. J. Herrera-Martin, I Castilla-Rodriguez, E. J. Gonzalez, N. Martin-Dorta
Summary: Building Information Modeling (BIM) has revolutionized the construction industry by providing a platform for integrated design, modeling, asset planning, and collaboration. This article proposes a method for mapping BIM data into specific domain concepts and utilizing Semantic Web tools for data and information exchange. The proposed mapping enhances information and improves data integration in systems managing services or maintaining facilities and building infrastructures.
EGYPTIAN INFORMATICS JOURNAL
(2022)
Article
Computer Science, Theory & Methods
Ankur Lohachab, Saurabh Garg, Byeong Ho Kang, Muhammad Bilal Amin
Summary: The researchers designed a novel P2P energy trading framework to improve resource utilization and address the electricity crisis challenge, evaluating the results based on different system parameters for validation. Performance bottlenecks and optimal configurations were determined through independent investigations, with the use of benchmark tools aiding application designers and developers in selecting suitable implementation models.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Wenli Yang, Saurabh Garg, Zhiqiang Huang, Byeong Kang
Summary: Conversation systems often face challenges in knowledge management from multiple human experts. Current knowledge-based conversation systems are typically centralized on servers, leading to potential issues in transparency and security. Blockchain solutions are being proposed to enhance security and efficiency in various domains, but the selection of blockchain platforms for knowledge-based conversation systems is still under development. The proposed decision model in this paper utilizes multiple methods such as AHP, FAHP, and FTOPSIS to analyze and generate consistent results, aiding in the selection of blockchain platforms and improving decision-making efficiency.
KNOWLEDGE-BASED SYSTEMS
(2021)
Review
Environmental Sciences
Leonardo J. Gutierrez, Kashif Rabbani, Oluwashina Joseph Ajayi, Samson Kahsay Gebresilassie, Joseph Rafferty, Luis A. Castro, Oresti Banos
Summary: The rising global cases of mental illness pose an urgent health threat, while IoT technologies offer new capabilities in early patient care. This paper comprehensively surveys the intersection of IoT and mental health disorders, evaluating various platforms, methods, devices, and identifying potential challenges for effective IoT use in mental health care.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Editorial Material
Computer Science, Information Systems
Oresti Banos, Joseph Rafferty, Luis A. Castro
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
(2021)
Article
Computer Science, Artificial Intelligence
Oresti Banos, Alberto Calatroni, Miguel Damas, Hector Pomares, Daniel Roggen, Ignacio Rojas, Claudia Villalonga
Summary: This paper introduces an alternative approach for training recognition systems based on transfer learning, using system identification techniques to automatically translate signals from source sensor domain to target sensor domain. Two transfer models are proposed for recognition system translation based on either activity templates or activity models.
NEURAL PROCESSING LETTERS
(2021)
Article
Automation & Control Systems
Zeyi Liu, Fuyuan Xiao, Chin-Teng Lin, Byeong Ho Kang, Zehong Cao
Summary: This study proposes a representative value method for handling interval criteria, using neural networks to adjust parameters to enhance decision accuracy and effectiveness.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Hardware & Architecture
Khizar Hameed, Saurabh Garg, Muhammad Bilal Amin, Byeong Kang, Abid Khan
Summary: This paper presents an efficient scheme for detecting clone node attacks on mobile IoT networks by using semantic information to securely locate IoT devices. The proposed location proof mechanism combines location proofs and batch verification to accelerate the verification process at trusted nodes. Additionally, a model for selecting trustworthy IoT devices based on their capabilities is introduced for the location proof-verification procedure, resulting in high detection accuracy and reduced resource overheads.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Review
Computer Science, Theory & Methods
Ankur Lohachab, Saurabh Garg, Byeong Kang, Muhammad Bilal Amin, Junmin Lee, Shiping Chen, Xiwei Xu
Summary: The unprecedented attention towards blockchain technology is shaping the development of blockchain-enabled frameworks, but challenges in inter-blockchain communication hinder its wide-scale adoption. Blockchain Interoperability (BI) plays a crucial role in connecting disparate blockchains, yet there is a lack of comprehensive studies in this area. This article aims to articulate the potential of BI by discussing its importance, proposing a layered architecture for protocol development, and providing insights into current projects and future research challenges.
ACM COMPUTING SURVEYS
(2021)
Article
Computer Science, Hardware & Architecture
Ranesh Naha, Saurabh Garg, Sudheer Kumar Battula, Muhammad Bilal Amin, Dimitrios Georgakopoulos
Summary: This paper proposes a multiple linear regression-based resource allocation mechanism to run applications with energy-awareness in the Fog computing environment. By balancing the trade-off between energy-efficient allocation and application execution time, the proposed approach successfully achieves energy-awareness objectives and reduces delay, processing time, and SLA violations.
Article
Environmental Sciences
Eugenia Castilla, Juan Jose Escobar, Claudia Villalonga, Oresti Banos
Summary: Mental health disorders are increasingly affecting people worldwide, leading to more family members becoming caregivers. A digital system called HIGEA has been developed to help detect caregiver burden using a conversational agent. Preliminary results have shown that the system is useful and effective.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Leonardo J. Gutierrez, Luis A. Castro, Oresti Banos
Summary: Ecological momentary interventions (EMIs) are provided to patients in their daily lives and natural settings to improve self-management of health. Technologies like smartphones make delivering EMIs easier, offering psychological support to mental health patients in their everyday lives. This work discusses current and emerging technologies, as well as challenges and opportunities in the information content and delivery of EMIs for mental health care, providing potential avenues for future research.
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING & AMBIENT INTELLIGENCE (UCAMI 2022)
(2023)
Article
Computer Science, Information Systems
Leonardo J. Gutierrez, Luis A. Castro, Oresti Banos
Summary: The article presents the current situation of global mental disorders and the situation in Mexico. Through a qualitative study, the author concludes that there are challenges and opportunities in the application of pervasive technology in the field of mental health, which requires attention and solutions from the scientific community.
IEEE PERVASIVE COMPUTING
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Ciro Rodriguez-Leon, William Arevalo, Oresti Banos, Claudia Villalonga
Summary: This study experiment with different pre-trained convolutional neural network models to predict diabetic retinopathy, showing that no architecture outperforms in all evaluation metrics. MobileNetV2 model stands out from a balanced behavior perspective with almost half the execution time of the slowest CNNs and no overfitting in 20 learning epochs. InceptionResNetV2 excels in terms of best performance, with a Kappa coefficient of 0.7588.
ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2021, PT I
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Pablo Salgado, Oresti Banos, Claudia Villalonga
Summary: This research aims to develop a deep neural network model capable of recognizing conversational facial expressions which are prone to misinterpretation in individuals with autism spectrum disorder. Promising training results were achieved, but the model showed limited generalization, highlighting the need for better datasets before building a full-fledged support system for ASD.
ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2021, PT I
(2021)
